A sampling scheme for estimating the mean extractable phosphorus concentration of fields for environmental regulation

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Authors D. J. Brus, L. Spätjens, J. J. de Gruijter
Journal/Conference Name Geoderma
Paper Category
Paper Abstract A soil sampling scheme for estimating the mean extractable P concentration of fields is designed to be used as a tool for environmental regulation of the application rates of manure. The field to be sampled, is split up into geographically compact blocks of equal area that are used as strata. From each stratum one sampling point is selected by Simple Random Sampling. These samples are bulked into one composite for the field. The geographical stratification is performed by restricted least-squares clustering of raster cells using the coordinates of the midpoints as classification variables and the within-group sum of squares as the minimisation criterion. Using a variance model and a cost model, the numbers of sample points and laboratory analyses are optimised simultaneously, given a maximum allowed variance of the total error (sampling error plus measurement error). To predict the sampling variance, variograms have been estimated for 16 fields differing in land-use, soil parent material and phosphate level. A pooled relative variogram was used to predict the sampling variance for various sample sizes (5 to 50), field-areas (1 to 10 ha) and phosphate levels (for grassland 20 to 80 mg P 2 O 5 extracted in ammonimum lactate per 100 g soil, for arable land 20 to 80 mg P 2 O 5 extracted in water per 1 dm 3 soil). The cost model consists of three components: (i) fieldwork cost; (ii) field equipment cost and, (iii) laboratory cost. For the 16 fields, the predicted sampling variance of the Stratified Sampling design is 0.8 to 0.4 times the predicted variance of Simple Random Sampling if 40 points were sampled. To estimate the mean extractable P concentration with a total variance ≤9, replicate measurement of the composite only pays if the mean extractable P concentration of the field exceeds 40 to 50. This critical phosphate level increases with the maximum allowed variance of the total error.
Date of publication 1999
Code Programming Language R

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